\documentclass{article}
\usepackage[landscape, top=1.5in, bottom=1in, right=.5in, left=.5in]{geometry}
\usepackage{dcolumn}
\begin{document}
<<>>=
sum(princeton.29$female==1)/length(princeton.29$female)*100
sum(princeton.29$female==0)/length(princeton.29$female)*100
sum(princeton.29$race==5)/length(princeton.29$race)*100
mean(princeton.29$age)
sd(princeton.29$age)
sum(princeton.29$party_id==5)/length(princeton.29$party_id)*100

sum(princeton.29$intensity==3)/length(princeton.29$intensity)*100
sum(princeton.29$treatment=="Control")
@

Read in and replace missing data
<<>>=
require(knitr)
library(car)
library(stargazer)
library(MASS)
library(ggplot2)
setwd("~/Desktop/Dropbox/School/THESIS/Thesis Data")
p.full <- read.csv("princetondata.csv", header=TRUE)
p.full$rate_hard <- recode(p.full$rate_hard, "NA=99")
p.full$rate_soft <- recode(p.full$rate_soft, "NA=99")
p.full$knowledge_hard <- recode(p.full$knowledge_hard, "NA=99")
p.full$knowledge_soft <- recode(p.full$knowledge_soft, "NA=99")
@
Create full dataset, additional variables, adiitional datasets that subset for age, and an additional dataset that displays those who got the control treatment.
<<>>=
princeton <- subset(p.full, completion==1 & minorstatus==1 & citizenship==1 & consent==1)
princeton$female <- princeton$gender
princeton$white <- recode(princeton$race, "2:5=0")
princeton$hardnews <- ifelse(princeton$rate_hard!=99, 1, 0) #received hard treatment
princeton$softnews <- ifelse(princeton$rate_soft!=99, 1, 0) #received soft treatment
princeton$control <- ifelse(princeton$rate_soft==99 & princeton$rate_hard==99, 1, 0)

princeton$hardsoft <- ifelse(princeton$rate_soft!=99, 1, 
                              ifelse(princeton$rate_hard!=99, 0, NA))

princeton$treatment <- ifelse(princeton$rate_hard!=99, "Hard", 
                              ifelse(princeton$rate_soft!=99, "Soft", "Control"))
princeton$treatment <- as.factor(princeton$treatment)
princeton$knowledge_soft <- ifelse(princeton$knowledge_soft==2, 1, 0)
princeton$knowledge_hard <- ifelse(princeton$knowledge_hard==2, 1, 0)

#Additive index for Dem. Party evaluation (7-28 scale)
princeton$d_eval <- (princeton$dem_care + princeton$dem_honest + princeton$dem_inspiring 
                     + princeton$dem_knowledgeable + princeton$dem_decisive + 
                       princeton$dem_leader + princeton$dem_competent)

#Additive index for Rep. Party evaulation (7-28 scale)
princeton$r_eval <- (princeton$rep_care + princeton$rep_honest + princeton$rep_inspiring
                     + princeton$rep_knowledgeable + princeton$rep_decisive 
                     + princeton$rep_leader + princeton$rep_competent)

# Overall Party evaluation additive index (14-56 scale)
princeton$overall_eval <- (princeton$d_eval + princeton$r_eval)

# Party Intensity (PID folded)
princeton$intensity <- ifelse(princeton$party_id==1 | princeton$party_id==5, 3, 
                              ifelse(princeton$party_id==3, 1, 2))

#regular viewers of Daily Show
princeton$reg_tds <- ifelse(princeton$source_tds==4 | princeton$source_tds==3, 1, 0)

#convert variables to factors
princeton$systemtrust <- as.factor(princeton$systemtrust)
princeton$mediatrust <- as.factor(princeton$mediatrust)
princeton$mediacoverage <- as.factor(princeton$mediacoverage)
princeton$efficacy <- as.factor(princeton$efficacy)

#variable for enjoyment (movement from hard to soft)
princeton$enjoy[princeton$treatment=="Soft"] <- princeton$rate_soft[princeton$treatment=="Soft"]
princeton$enjoy[princeton$treatment=="Hard"] <- princeton$rate_hard[princeton$treatment=="Hard"]
princeton$enjoy <- as.factor(princeton$enjoy)
summary(princeton$enjoy)

#variable for knowledge (movement from hard to soft)
princeton$knowledge[princeton$treatment=="Soft"] <- princeton$knowledge_soft[princeton$treatment=="Soft"]
princeton$knowledge[princeton$treatment=="Hard"] <- princeton$knowledge_hard[princeton$treatment=="Hard"]
princeton$knowledge <- as.factor(princeton$knowledge)
summary(princeton$knowledge)

#Subset of respondents who are 29 or younger
princeton.29 <- subset(princeton, age<=29)

#Subset of respondents who are 24 or younger
princeton.24 <- subset(princeton, age<=24)

#subset of respondents who got control treatment
princeton.control <- subset(princeton, treatment=="Control")

#subset of regular TDS viewers
princeton.reg <- subset(princeton, reg_tds==1)
princeton.reg29 <- subset(princeton.29, reg_tds==1)
princeton.reg24 <- subset(princeton.24, reg_tds==1)

#subset of non-TDS viewers
princeton.non <- subset(princeton, reg_tds==0)
princeton.non29 <- subset(princeton.29, reg_tds==0)
princeton.non24 <- subset(princeton.24, reg_tds==0)
@
Manipulation check
<<>>=

t.test(princeton$rate_soft[princeton$treatment=="Soft"], 
       princeton$rate_hard[princeton$treatment=="Hard"])

t.test(princeton.29$rate_soft[princeton.29$treatment=="Soft"], 
       princeton.29$rate_hard[princeton.29$treatment=="Hard"])

t.test(princeton.24$rate_soft[princeton.24$treatment=="Soft"], 
       princeton.24$rate_hard[princeton.24$treatment=="Hard"])

enj1 <- polr(enjoy ~ hardsoft + race + female + party_id + intensity,
               method=c("probit"), data=princeton)
summary(enj1)

enj2 <- polr(enjoy ~ hardsoft + race + female + party_id + intensity,
               method=c("probit"), data=princeton.29)
summary(enj2)

enj3 <- polr(enjoy ~ hardsoft + race + female + party_id + intensity,
               method=c("probit"), data=princeton.24)
summary(enj3)
@
Knowledge check (recognition)
<<>>=
t.test(princeton$knowledge_hard[princeton$treatment=="Hard"],
       princeton$knowledge_soft[princeton$treatment=="Soft"])

t.test(princeton.29$knowledge_hard[princeton.29$treatment=="Hard"],
       princeton.29$knowledge_soft[princeton.29$treatment=="Soft"])

t.test(princeton.24$knowledge_hard[princeton.24$treatment=="Hard"],
       princeton.24$knowledge_soft[princeton.24$treatment=="Soft"])
@
Lm tests for party evaluations (based off of Baumgartner and Morris) - full dataset
<<>>=
eval1 <- lm(r_eval ~ treatment + white + female + party_id + intensity, data=princeton)
eval2 <- lm(d_eval ~ treatment + white + female + party_id + intensity, data=princeton)
eval3 <- lm(overall_eval ~ treatment + white + female + party_id + intensity, 
            data=princeton)
@
<<results='asis'>>=
stargazer(eval1, eval2, eval3, 
          title="Party Evaluations by Experimental Condition 
          (Based on Baumgartner Model)", 
          no.space=TRUE, 
          dep.var.labels=c("Republican Party Evaluation", "Democratic Party Evaluation",
                           "Overall Party Evaluation"), 
          covariate.labels=c("The Daily Show condition", "CBS News condition", 
                             "Race", "Female", "Republican", 
                             "Intensity"), 
          single.row=TRUE, 
          model.numbers=FALSE, 
          order=c(2, 1, 3, 4, 5, 6),
          apply.p=function(x){x/2},
          notes=c("(One-tailed test)", "Republican (1=strong Dem. to 5=Strong Rep.)",
                  "Race (1=White, 0=non-White)","Intensity (PID folded)"),
          notes.align="r",
          align=TRUE,
          omit.stat=c("f", "rsq", "ser"))
@
Lm tests for party evaluations (based off of Baumgartner and Morris) - 29 and younger
<<>>=
eval4 <- lm(r_eval ~ treatment + white + female + party_id + intensity, data=princeton.29)
eval5 <- lm(d_eval ~ treatment + white + female + party_id + intensity, data=princeton.29)
eval6 <- lm(overall_eval ~ treatment + white + female + party_id + intensity, 
            data=princeton.29)

@
<<results='asis'>>=
stargazer(eval4, eval5, eval6, 
          title="Party Evaluations by Experimental Condition 
          (Based on Baumgartner Model)", 
          no.space=TRUE, 
          dep.var.labels=c("Republican Party Evaluation", "Democratic Party Evaluation",
                           "Overall Party Evaluation"), 
          covariate.labels=c("The Daily Show condition", "CBS News condition", 
                             "Race", "Female", "Republican", 
                             "Party Intensity"), 
          single.row=TRUE, 
          model.numbers=FALSE, 
          order=c(2, 1, 3, 4, 5, 6),
          apply.p=function(x){x/2},
          notes=c("Ages 29 or younger (One-tailed test)","Republican 
                  (1=strong Dem. to 5=Strong Rep.)","Race (1=White, 0=non-White)",
                  "Intensity (PID folded)"),
          notes.align="r",
          align=TRUE,
          omit.stat=c("f", "rsq", "ser"))
@
Lm tests for party evaluations (based off of Baumgartner and Morris) - 24 and younger
<<>>=
eval7 <- lm(r_eval ~ treatment + white + female + party_id + intensity, data=princeton.24)
eval8 <- lm(d_eval ~ treatment + white + female + party_id + intensity, data=princeton.24)
eval9 <- lm(overall_eval ~ treatment + white + female + party_id + intensity, 
            data=princeton.24)
@
<<results='asis'>>=
stargazer(eval7, eval8, eval9, 
          title="Party Evaluations by Experimental Condition 
          (Based on Baumgartner Model)", 
          no.space=TRUE, 
          dep.var.labels=c("Republican Party Evaluation", "Democratic Party Evaluation",
                           "Overall Party Evaluation"), 
          covariate.labels=c("The Daily Show condition", "CBS News condition", 
                             "Race", "Female", "Republican", 
                             "Party Intensity"), 
          single.row=TRUE, 
          model.numbers=FALSE, 
          order=c(2, 1, 3, 4, 5, 6),
          apply.p=function(x){x/2},
          notes=c("Ages 24 or younger (One-tailed test)","Republican 
                  (1=strong Dem. to 5=Strong Rep.)","Race (1=White, 0=non-White)",
                  "Intensity (PID folded)"),
          notes.align="r",
          align=TRUE,
          omit.stat=c("f", "rsq", "ser"))
@
Lm test for party evaluations with additional controls (age and education) - full dataset
<<>>=
eval10 <- lm(r_eval ~ treatment + white + female + party_id + intensity + age 
             + education, data=princeton)
eval11 <- lm(d_eval ~ treatment + white + female + party_id + intensity + age 
             + education, data=princeton)
eval12 <- lm(overall_eval ~ treatment + white + female + party_id + intensity + age 
             +education, data=princeton)
@
<<results='asis'>>=
stargazer(eval10, eval11, eval12, 
          title="Party Evaluations by Experimental Condition with Additional Controls", 
          no.space=TRUE, 
          dep.var.labels=c("Republican Party Evaluation", "Democratic Party Evaluation",
                           "Overall Party Evaluation"), 
          covariate.labels=c("The Daily Show condition", "CBS News condition", 
                             "Race", "Female", 
                             "Republican", "Party Intensity", "Age", "Education"), 
          single.row=TRUE, 
          model.numbers=FALSE, 
          order=c(2, 1, 3, 4, 5, 6, 7, 8),
          apply.p=function(x){x/2},
          notes=c("(One-tailed test)","Republican 
                  (1=strong Dem. to 5=Strong Rep.)","Race (1=White, 0=non-White)",
                  "Intensity (PID folded)"),
          notes.align="r",
          align=TRUE,
          omit.stat=c("f", "rsq", "ser"))
@
Lm test for party evaluations with additional controls (age and education) - 29 and younger
<<>>=
eval13 <- lm(r_eval ~ treatment + white + female + party_id + intensity + age 
             + education, data=princeton.29)
eval14 <- lm(d_eval ~ treatment + white + female + party_id + intensity + age 
             + education, data=princeton.29)
eval15 <- lm(overall_eval ~ treatment + white + female + party_id + intensity + age + 
              education, data=princeton.29)
@
<<results='asis'>>=
stargazer(eval13, eval14, eval15, 
          title="Party Evaluations by Experimental Condition with Additional Controls", 
          no.space=TRUE, 
          dep.var.labels=c("Republican Party Evaluation", "Democratic Party Evaluation",
                           "Overall Party Evaluation"), 
          covariate.labels=c("The Daily Show condition", "CBS News condition", 
                             "Race", "Female", 
                             "Republican", "Party Intensity", "Age", "Education"), 
          single.row=TRUE, 
          model.numbers=FALSE, 
          order=c(2, 1, 3, 4, 5, 6, 7, 8),
          apply.p=function(x){x/2},
          notes=c("Ages 29 or younger (One-tailed test)","Republican 
                  (1=strong Dem. to 5=Strong Rep.)","Race (1=White, 0=non-White)",
                  "Intensity (PID folded)"),
          notes.align="r",
          align=TRUE,
          omit.stat=c("f", "rsq", "ser"))
@
Lm test for party evaluations with additional controls (age and education) - 24 and younger
 <<>>=
eval16 <- lm(r_eval ~ treatment + white + female + party_id + intensity + age 
             +education,data=princeton.24)
eval17 <- lm(d_eval ~ treatment + white + female + party_id + intensity + age 
             +education, data=princeton.24)
eval18 <- lm(overall_eval ~ treatment + white + female + party_id + intensity + age + 
              education, data=princeton.24)
@
<<results='asis'>>=
stargazer(eval16, eval17, eval18, 
          title="Party Evaluations by Experimental Condition with Additional Controls", 
          no.space=TRUE, 
          dep.var.labels=c("Republican Party Evaluation", "Democratic Party Evaluation",
                           "Overall Party Evaluation"), 
          covariate.labels=c("The Daily Show condition", "CBS News condition", 
                             "Race", "Female", 
                             "Republican", "Party Intensity", "Age", "Education"), 
          single.row=TRUE, 
          model.numbers=FALSE, 
          order=c(2, 1, 3, 4, 5, 6, 7, 8),
          apply.p=function(x){x/2},
          notes=c("Ages 24 or younger (One-tailed test)","Republican 
                  (1=strong Dem. to 5=Strong Rep.)","Race (1=White, 0=non-White)",
                  "Intensity (PID folded)"),
          notes.align="r",
          align=TRUE,
          omit.stat=c("f", "rsq", "ser"))
@
Tests on political efficacy (Baumgartner Method) - full dataset
<<>>=
trust1 <- polr(systemtrust ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton)
mt1 <- polr(mediatrust ~ treatment + race + female + party_id + intensity, 
            method=c("probit"), data=princeton)
mc1 <- polr(mediacoverage ~ treatment + race + female + party_id + intensity,
            method=c("probit"), data=princeton)
eff1 <- polr(efficacy ~ treatment + race + female + party_id + intensity,
            method=c("probit"), data=princeton)
@
<<results='asis'>>=
stargazer(trust1, mt1, mc1, eff1,
          title=c("Perceptions of Electoral System, and Media by Experimental Condition
                  (Based on Baumgartner Model)"),
          no.space=TRUE,
          order=c(2, 1, 3, 4, 5, 6),
          dep.var.labels=c("Faith in
                          Electoral System", "Trust in
                          News Media", "
                          Political Coverage", "Efficacy"),
          covariate.labels=c("The Daily Show Condition", "CBS News Condition",
                             "Race", "Female", "Republican", "Intensity"),
          single.row=TRUE,
          model.numbers=FALSE,
          apply.p=function(x){x/2},
          notes=c("(One-tailed test)","Republican 
                  (1=strong Dem. to 5=Strong Rep.)","Race (1=White, 0=non-White)",
                  "Intensity (PID folded)"),
          notes.align="r",
          align=TRUE,
          column.sep.width=c("-10pt"))
@
Tests on political efficacy (Baumgartner Method) - 29 and younger
<<>>=
trust2 <- polr(systemtrust ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.29)
mt2 <- polr(mediatrust ~ treatment + race + female + party_id + intensity, 
            method=c("probit"), data=princeton.29)
mc2 <- polr(mediacoverage ~ treatment + race + female + party_id + intensity,
            method=c("probit"), data=princeton.29)
eff2 <- polr(efficacy ~ treatment + race + female + party_id + intensity,
            method=c("probit"), data=princeton.29)
@
<<results='asis'>>=
stargazer(trust2, mt2, mc2, eff2,
          title=c("Perceptions of Electoral System, and Media by Experimental Condition
                  (Based on Baumgartner Model)"),
          no.space=TRUE,
          order=c(2, 1, 3, 4, 5, 6),
          dep.var.labels=c("Faith in
                          Electoral System", "Trust in
                          News Media", "
                          Political Coverage", "Efficacy"),
          covariate.labels=c("The Daily Show Condition", "CBS News Condition",
                             "Race", "Female", "Repbulican", "Intensity"),
          single.row=TRUE,
          model.numbers=FALSE,
          apply.p=function(x){x/2},
          notes=c("Ages 29 and younger (One-tailed test)","Republican 
                  (1=strong Dem. to 5=Strong Rep.)","Race (1=White, 0=non-White)",
                  "Intensity (PID folded)"),
          notes.align="r",
          align=TRUE,
          column.sep.width=c("-10pt"))
@
Tests on political efficacy (Baumgartner Method) - 24 and younger
<<>>=
trust3 <- polr(systemtrust ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.24)
mt3 <- polr(mediatrust ~ treatment + race + female + party_id + intensity, 
            method=c("probit"), data=princeton.24)
mc3 <- polr(mediacoverage ~ treatment + race + female + party_id + intensity,
            method=c("probit"), data=princeton.24)
eff3 <- polr(efficacy ~ treatment + race + female + party_id + intensity,
            method=c("probit"), data=princeton.24)
@
<<results='asis'>>=
stargazer(trust3, mt3, mc3, eff3,
          title=c("Perceptions of Electoral System, and Media by Experimental Condition
                  (Based on Baumgartner Model)"),
          no.space=TRUE,
          order=c(2, 1, 3, 4, 5, 6),
          dep.var.labels=c("Faith in
                          Electoral System", "Trust in
                          News Media", "
                          Political Coverage", "Efficacy"),
          covariate.labels=c("The Daily Show Condition", "CBS News Condition",
                             "Race", "Female", "Repbulican", "Intensity"),
          single.row=TRUE,
          model.numbers=FALSE,
          apply.p=function(x){x/2},
          notes=c("Ages 24 and younger (One-tailed test)","Republican 
                  (1=strong Dem. to 5=Strong Rep.)","Race (1=White, 0=non-White)",
                  "Intensity (PID folded)"),
          notes.align="r",
          align=TRUE,
          column.sep.width=c("-10pt"))
@
Tests on efficacy with additional controls (age and education) - full dataset
<<>>=
trust4 <- polr(systemtrust ~ treatment + race + female + party_id + intensity + age
               + education, method=c("probit"), data=princeton)
mt4 <- polr(mediatrust ~ treatment + race + female + party_id + intensity + age
            + education, method=c("probit"), data=princeton)
mc4 <- polr(mediacoverage ~ treatment + race + female + party_id + intensity + age
            + education, method=c("probit"), data=princeton)
eff4 <- polr(efficacy ~ treatment + race + female + party_id + intensity + age
             + education, method=c("probit"), data=princeton)
@
<<results='asis'>>=
stargazer(trust4, mt4, mc4, eff4,
          title=c("Perceptions of Electoral System, Media, and Internal Efficacy by
                  Experimental Condition with Additional Controls"),
          no.space=TRUE,
          order=c(2, 1, 3, 4, 5, 6),
          dep.var.labels=c("Faith in
                          Electoral System", "Trust in
                          News Media", "
                          Political Coverage", "Efficacy"),
          covariate.labels=c("The Daily Show Condition", "CBS News Condition",
                             "Race", "Female", "Repbulican", "Intensity",
                             "Age", "Education"),
          single.row=TRUE,
          model.numbers=FALSE,
          apply.p=function(x){x/2},
          notes=c("(One-tailed test)", "Republican 
                  (1=strong Dem. to 5=Strong Rep.)","Race (1=White, 0=non-White)",
                  "Intensity (PID folded)"),
          notes.align="r",
          align=TRUE,
          column.sep.width=c("-10pt"))
@
Tests on efficacy with additional controls (age and education) - 29 and younger
<<>>=
trust5 <- polr(systemtrust ~ treatment + race + female + party_id + intensity + age
               + education, method=c("probit"), data=princeton.29)
mt5 <- polr(mediatrust ~ treatment + race + female + party_id + intensity + age
            + education, method=c("probit"), data=princeton.29)
mc5 <- polr(mediacoverage ~ treatment + race + female + party_id + intensity + age
            + education, method=c("probit"), data=princeton.29)
eff5 <- polr(efficacy ~ treatment + race + female + party_id + intensity + age
             + education, method=c("probit"), data=princeton.29)
@
<<results='asis'>>=
stargazer(trust5, mt5, mc5, eff5,
          title=c("Perceptions of Electoral System, Media, and Internal Efficacy by
                  Experimental Condition with Additional Controls"),
          no.space=TRUE,
          order=c(2, 1, 3, 4, 5, 6),
          dep.var.labels=c("Faith in
                          Electoral System", "Trust in
                          News Media", "
                          Political Coverage", "Efficacy"),
          covariate.labels=c("The Daily Show Condition", "CBS News Condition",
                             "Race", "Female", "Repbulican", "Intensity",
                             "Age", "Education"),
          single.row=TRUE,
          model.numbers=FALSE,
          apply.p=function(x){x/2},
          notes=c("Ages 29 and younger (One-tailed test)","Republican 
                  (1=strong Dem. to 5=Strong Rep.)","Race (1=White, 0=non-White)",
                  "Intensity (PID folded)"),
          notes.align="r",
          align=TRUE,
          column.sep.width=c("-10pt"))
@
Tests on efficacy with additional controls (age and education) - 24 and younger
<<>>=
trust6 <- polr(systemtrust ~ treatment + race + female + party_id + intensity + age
               + education, method=c("probit"), data=princeton.24)
mt6 <- polr(mediatrust ~ treatment + race + female + party_id + intensity + age
            + education, method=c("probit"), data=princeton.24)
mc6 <- polr(mediacoverage ~ treatment + race + female + party_id + intensity + age
            + education, method=c("probit"), data=princeton.24)
eff6 <- polr(efficacy ~ treatment + race + female + party_id + intensity + age
             + education, method=c("probit"), data=princeton.24)
@
<<results='asis'>>=
stargazer(trust6, mt6, mc6, eff6,
          title=c("Perceptions of Electoral System, Media, and Internal Efficacy by
                  Experimental Condition with Additional Controls"),
          no.space=TRUE,
          order=c(2, 1, 3, 4, 5, 6),
          dep.var.labels=c("Faith in
                          Electoral System", "Trust in
                          News Media", "
                          Political Coverage", "Efficacy"),
          covariate.labels=c("The Daily Show Condition", "CBS News Condition",
                             "Race", "Female", "Repbulican", "Intensity",
                             "Age", "Education"),
          single.row=TRUE,
          model.numbers=FALSE,
          apply.p=function(x){x/2},
          notes=c("Ages 24 and younger (One-tailed test)","Republican 
                  (1=strong Dem. to 5=Strong Rep.)","Race (1=White, 0=non-White)",
                  "Intensity (PID folded)"),
          notes.align="r",
          align=TRUE,
          column.sep.width=c("-10pt"))
@
Candidate Evaluations between regular TDS viewers and non-viewers
<<>>=
eval19 <- lm(r_eval~treatment + race + female + party_id + intensity, 
             data=princeton.reg)
eval20 <- lm(r_eval~treatment + race + female + party_id + intensity, 
             data=princeton.non)
eval21 <- lm(d_eval~treatment + race + female + party_id + intensity, 
             data=princeton.reg)
eval22 <- lm(d_eval~treatment + race + female + party_id + intensity, 
             data=princeton.non)
eval23 <- lm(overall_eval~treatment + race + female + party_id + intensity, 
             data=princeton.reg)
eval24 <- lm(overall_eval~treatment + race + female + party_id + intensity, 
             data=princeton.non)
@
<<results='asis'>>=
stargazer(eval20, eval19, eval22, eval21, eval24, eval23,
          title="Candidate Evaluations by Experimental Condition, Viewer and Non-viewer",
          covariate.labels=c("The Daily Show condition", "CBS News conditions", "Race",
                           "Female", "Republican", "Party Intensity"),
          dep.var.labels=c("Republican Eval.",  "Democratic Eval.", "Overall Eval."),
          column.labels=c("Non-viewer", "Viewer", "Non-viewer", "Viewer", 
                          "Non-viewer", "Viewer"),
          column.separate=c(1,1,1,1,1,1),
          order=c(2, 1, 3, 4, 5, 6),
          model.numbers=FALSE,
          apply.p=function(x){x/2},
          notes=c("(One-tailed test)","Republican 
                  (1=strong Dem. to 5=Strong Rep.)","Race (1=White, 0=non-White)",
                  "Intensity (PID folded)"),
          notes.align="r",
          align=TRUE,
          omit.stat=c("f", "rsq", "ser"),
          column.sep.width=c("5pt"))
@
Viewers v. non-viewers, 29 years and younger
<<>>=
eval25 <- lm(r_eval~treatment + race + female + party_id + intensity, 
             data=princeton.reg29)
eval26 <- lm(r_eval~treatment + race + female + party_id + intensity, 
             data=princeton.non29)
eval27 <- lm(d_eval~treatment + race + female + party_id + intensity, 
             data=princeton.reg29)
eval28 <- lm(d_eval~treatment + race + female + party_id + intensity, 
             data=princeton.non29)
eval29 <- lm(overall_eval~treatment + race + female + party_id + intensity, 
             data=princeton.reg29)
eval30 <- lm(overall_eval~treatment + race + female + party_id + intensity, 
             data=princeton.non29)
@
<<results='asis'>>=
stargazer(eval26, eval25, eval28, eval27, eval30, eval29,
          title="Candidate Evaluations by Experimental Condition, Viewer and Non-viewer",
          covariate.labels=c("The Daily Show condition", "CBS News conditions", "Race",
                           "Female", "Republican", "Party Intensity"),
          dep.var.labels=c("Republican Eval.",  "Democratic Eval.", "Overall Eval."),
          column.labels=c("Non-viewer", "Viewer", "Non-viewer", "Viewer", 
                          "Non-viewer", "Viewer"),
          column.separate=c(1,1,1,1,1,1),
          order=c(2, 1, 3, 4, 5, 6),
          model.numbers=FALSE,
          apply.p=function(x){x/2},
          notes=c("Ages 29 and Younger (One-tailed test)","Republican 
                  (1=strong Dem. to 5=Strong Rep.)","Race (1=White, 0=non-White)",
                  "Intensity (PID folded)"),
          notes.align="r",
          align=TRUE,
          omit.stat=c("f", "rsq", "ser"),
          column.sep.width=c("5pt"))
@

Viewers v. non viewers, 24 years and younger
<<>>=
eval31 <- lm(r_eval~treatment + race + female + party_id + intensity, 
             data=princeton.reg24)
eval32 <- lm(r_eval~treatment + race + female + party_id + intensity, 
             data=princeton.non24)
eval33 <- lm(d_eval~treatment + race + female + party_id + intensity, 
             data=princeton.reg24)
eval34 <- lm(d_eval~treatment + race + female + party_id + intensity, 
             data=princeton.non24)
eval35 <- lm(overall_eval~treatment + race + female + party_id + intensity, 
             data=princeton.reg24)
eval36 <- lm(overall_eval~treatment + race + female + party_id + intensity, 
             data=princeton.non24)
@
<<results='asis'>>=
stargazer(eval32, eval31, eval34, eval33, eval36, eval35,
          title="Candidate Evaluations by Experimental Condition, Viewer and Non-viewer",
          covariate.labels=c("The Daily Show condition", "CBS News conditions", "Race",
                           "Female", "Republican", "Party Intensity"),
          dep.var.labels=c("Republican Eval.",  "Democratic Eval.", "Overall Eval."),
          column.labels=c("Non-viewer", "Viewer", "Non-viewer", "Viewer", 
                          "Non-viewer", "Viewer"),
          column.separate=c(1,1,1,1,1,1),
          order=c(2, 1, 3, 4, 5, 6),
          model.numbers=FALSE,
          apply.p=function(x){x/2},
          notes=c("24 years and younger (One-tailed test)","Republican 
                  (1=strong Dem. to 5=Strong Rep.)","Race (1=White, 0=non-White)",
                  "Intensity (PID folded)"),
          notes.align="r",
          align=TRUE,
          omit.stat=c("f", "rsq", "ser"),
          column.sep.width=c("5pt"))
@

Efficacy tests between regular TDS viewers and non-viewers
<<>>=
trust7 <- polr(systemtrust ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.non)
trust8 <- polr(systemtrust ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.reg)
mt7 <- polr(mediatrust ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.non)
mt8 <- polr(mediatrust ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.reg)
mc7 <- polr(mediacoverage ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.non)
mc8 <- polr(mediacoverage ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.reg)
eff7 <- polr(efficacy ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.non)
eff8 <- polr(efficacy ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.reg)
@
<<results='asis'>>=
stargazer(trust7, trust8, mt7, mt8, mc7, mc8, eff7, eff8,
          title=c("Perceptions of Electoral System, Media, and Internal Efficacy
                  by Experimental Condition, Viewer and Non-viewer"),
          covariate.labels=c("The Daily Show condition", "CBS News conditions", "Race",
                           "Female", "Republican", "Party Intensity"),
          dep.var.labels=c("Faith in
                          Electoral System", "Trust in
                          News Media", "
                          Political Coverage", "Efficacy"),
          column.labels=c("Non-viewer", "Viewer", "Non-viewer", "Viewer", 
                          "Non-viewer", "Viewer", "Non-viewer", "Viewer"),
          column.separate=c(1,1,1,1,1,1,1,1),
          order=c(2, 1, 3, 4, 5, 6),
          model.numbers=FALSE,
          apply.p=function(x){x/2},
          notes=c("(One-tailed test)","Republican 
                  (1=strong Dem. to 5=Strong Rep.)","Race (1=White, 0=non-White)",
                  "Intensity (PID folded)"),
          notes.align="r",
          align=TRUE,
          omit.stat=c("f", "rsq", "ser"),
          column.sep.width=c("5pt"),
          font.size="small")
@
Efficacy tests between regular TDS viewers and non-viewers (29 and younger)

<<>>=
trust9 <- polr(systemtrust ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.non29)
trust10 <- polr(systemtrust ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.reg29)
mt9 <- polr(mediatrust ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.non29)
mt10 <- polr(mediatrust ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.reg29)
mc9 <- polr(mediacoverage ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.non29)
mc10 <- polr(mediacoverage ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.reg29)
eff9 <- polr(efficacy ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.non29)
eff10 <- polr(efficacy ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.reg29)
@
<<results='asis'>>=
stargazer(trust9, trust10, mt9, mt10, mc9, mc10, eff9, eff10,
          title=c("Perceptions of Electoral System, Media, and Internal Efficacy
                  by Experimental Condition, Viewer and Non-viewer"),
          covariate.labels=c("The Daily Show condition", "CBS News conditions", "Race",
                           "Female", "Republican", "Party Intensity"),
          dep.var.labels=c("Faith in
                          Electoral System", "Trust in
                          News Media", "
                          Political Coverage", "Efficacy"),
          column.labels=c("Non-viewer", "Viewer", "Non-viewer", "Viewer", 
                          "Non-viewer", "Viewer", "Non-viewer", "Viewer"),
          column.separate=c(1,1,1,1,1,1,1,1),
          order=c(2, 1, 3, 4, 5, 6),
          model.numbers=FALSE,
          apply.p=function(x){x/2},
          notes=c("Ages 29 and younger (One-tailed test)","Republican 
                  (1=strong Dem. to 5=Strong Rep.)","Race (1=White, 0=non-White)",
                  "Intensity (PID folded)"),
          notes.align="r",
          align=TRUE,
          omit.stat=c("f", "rsq", "ser"),
          column.sep.width=c("5pt"),
          font.size="small")
@
Efficacy tests between regular TDS viewers and non-viewers (24 and younger)
<<>>=
trust11 <- polr(systemtrust ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.non24)
trust12 <- polr(systemtrust ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.reg24)
mt11 <- polr(mediatrust ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.non24)
mt12 <- polr(mediatrust ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.reg24)
mc11 <- polr(mediacoverage ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.non24)
mc12 <- polr(mediacoverage ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.reg24)
eff11 <- polr(efficacy ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.non24)
eff12 <- polr(efficacy ~ treatment + race + female + party_id + intensity,
               method=c("probit"), data=princeton.reg24)
@
<<results='asis'>>=
stargazer(trust11, trust12, mt11, mt12, mc11, mc12, eff11, eff12,
          title=c("Perceptions of Electoral System, Media, and Internal Efficacy
                  by Experimental Condition, Viewer and Non-viewer"),
          covariate.labels=c("The Daily Show condition", "CBS News conditions", "Race",
                           "Female", "Republican", "Party Intensity"),
          dep.var.labels=c("Faith in
                          Electoral System", "Trust in
                          News Media", "
                          Political Coverage", "Efficacy"),
          column.labels=c("Non-viewer", "Viewer", "Non-viewer", "Viewer", 
                          "Non-viewer", "Viewer", "Non-viewer", "Viewer"),
          column.separate=c(1,1,1,1,1,1,1,1),
          order=c(2, 1, 3, 4, 5, 6),
          model.numbers=FALSE,
          apply.p=function(x){x/2},
          notes=c("Ages 24 and younger (One-tailed test)","Republican 
                  (1=strong Dem. to 5=Strong Rep.)","Race (1=White, 0=non-White)",
                  "Intensity (PID folded)"),
          notes.align="r",
          align=TRUE,
          omit.stat=c("f", "rsq", "ser"),
          column.sep.width=c("5pt"),
          font.size="small")
@

Candidate evaluation based on media exposure (control group) - full control dataset
<<>>=
c1 <- lm(r_eval ~ source_latenight + source_tds + source_orf + source_lwt + 
           source_netnews + source_localnews + source_newspaper + race + 
           female + party_id, data=princeton.control)
c2 <- lm(d_eval ~ source_latenight + source_tds + source_orf + source_lwt + 
           source_netnews + source_localnews + source_newspaper + race + 
           female + party_id, data=princeton.control)
c3 <- lm(overall_eval ~ source_latenight + source_tds + source_orf + source_lwt + 
           source_netnews + source_localnews + source_newspaper + race + 
           female + party_id, data=princeton.control)
@
<<results='asis'>>=
stargazer(c1, c2, c3,
          title=c("Candidate Evaluations by Media Exposure (control group only)"),
          no.space=TRUE,
          dep.var.labels=c("Republican Eval.", "Democratic Eval.",
                            "Overall Eval."),
          covariate.labels=c("Fallon and/or Kimmel", "The Daily Show", 
                             "The O'Reilly Factor", "Last Week Tonight",
                             "Network evening news", "Local evening news", 
                             "Daily newspaper", "White", "Female", "Repbulican"),
          single.row=TRUE,
          model.numbers=FALSE,
          apply.p=function(x){x/2},
          notes=c("(One-tailed test)","Republican 
                  (1=strong Dem. to 5=Strong Rep.)","Race (1=White, 0=non-White)",
                  "Intensity (PID folded)"),
          notes.align="r",
          align=TRUE,
          column.sep.width=c("-10pt"),
          omit.stat=c("f", "rsq", "ser"))
@
Efficacy evaluations based on media exposure (control group) - full control dataset
<<>>=
c4 <- polr(systemtrust ~ source_latenight + source_tds + source_orf + source_lwt + 
           source_netnews + source_localnews + source_newspaper + race + 
           female + party_id, method=c("probit"), data=princeton.control)
c5 <- polr(mediatrust ~ source_latenight + source_tds + source_orf + source_lwt + 
           source_netnews + source_localnews + source_newspaper + race + 
           female + party_id, method=c("probit"), data=princeton.control)
c6 <- polr(mediacoverage ~ source_latenight + source_tds + source_orf + source_lwt + 
           source_netnews + source_localnews + source_newspaper + race + 
           female + party_id, method=c("probit"), data=princeton.control)
c7 <- polr(efficacy ~ source_latenight + source_tds + source_orf + source_lwt + 
           source_netnews + source_localnews + source_newspaper + race + 
           female + party_id, method=c("probit"), data=princeton.control)
@
<<results='asis'>>=
stargazer(c4, c5, c6, c7,
          title=c("Perceptions of Electoral System, Media, and Internal Efficacy
                  by Media Exposure (control group only)"),
          no.space=TRUE,
          dep.var.labels=c("Faith in
                          Electoral System", "Trust in
                          News Media", "
                          Political Coverage", "Efficacy"),
          covariate.labels=c("Fallon and/or Kimmel", "The Daily Show", 
                             "The O'Reilly Factor", "Last Week Tonight",
                             "Network evening news", "Local evening news", 
                             "Daily newspaper", "White", "Female", "Repbulican"),
          single.row=TRUE,
          model.numbers=FALSE,
          apply.p=function(x){x/2},
          notes=c("(One-tailed test)","Republican 
                  (1=strong Dem. to 5=Strong Rep.)","Race (1=White, 0=non-White)",
                  "Intensity (PID folded)"),
          notes.align="r",
          align=TRUE,
          column.sep.width=c("10pt"))
@
\end{document}